Card: cleaner examples figure and usage

README.md

@@ -46,25 +46,28 @@ SQuID asks vision-language models to measure satellite images: count objects, co
 from datasets import load_dataset
 
 bench = load_dataset("PeterAM4/SQuID", "benchmark", split="test")
+
 ex = bench[0]
-ex["image"], ex["mask"]        # PIL images (mask is None for NAIP)
-ex["question"], ex["answer"]   # 'What percentage of the image is agricultural land within 50m of water bodies? (GSD: 0.3m)', '29.32'
+ex["question"]   # 'What percentage of the image is agricultural land within 50m of water bodies? (GSD: 0.3m)'
+ex["answer"]     # '29.32'
+ex["image"]      # PIL image; ex["mask"] is its reference mask (None for NAIP)
 ```
 
-Score a prediction:
+A numeric answer is correct inside its accepted range; the others must match exactly:
 
 ```python
 def is_correct(pred, ex):
     lo, hi = ex["acceptable_range_lower"], ex["acceptable_range_upper"]
-    if lo is None:                       # yes/no (1/0) and connected/fragmented
+    if lo is None:  # yes/no (1/0), connected/fragmented
         return str(pred) == ex["answer"]
     return lo <= float(pred) <= hi
 ```
 
-The `train` config lists 75,687 questions whose `image` and `mask` are file paths in this repository. Download the files with:
+The `train` config holds 75,687 questions whose `image` and `mask` are paths in this repository:
 
 ```python
 from huggingface_hub import snapshot_download
+
 snapshot_download("PeterAM4/SQuID", repo_type="dataset", local_dir="data")
 ```